4 citations · 11 across the 19 of their papers we have counts for
5 papers · 1 filter
Boosting Multi-Speaker Expressive Speech Synthesis with Semi-supervised Contrastive Learning
Xinfa Zhu, Yuke Li, Yi Lei +3
This paper aims to build a multi-speaker expressive TTS system, synthesizing a target speaker's speech with multiple styles and emotions. To this end, we propose a novel contrastiv…
PromptVC: Flexible Stylistic Voice Conversion in Latent Space Driven by Natural Language Prompts
Jixun Yao, Yuguang Yang, Yi Lei +7
Style voice conversion aims to transform the style of source speech to a desired style according to real-world application demands. However, the current style voice conversion appr…
METTS: Multilingual Emotional Text-to-Speech by Cross-speaker and Cross-lingual Emotion Transfer
Xinfa Zhu, Yi Lei, Tao Li +4
Previous multilingual text-to-speech (TTS) approaches have considered leveraging monolingual speaker data to enable cross-lingual speech synthesis. However, such data-efficient app…
Multi-Speaker Expressive Speech Synthesis via Multiple Factors Decoupling
Xinfa Zhu, Yi Lei, Kun Song +3
This paper aims to synthesize the target speaker's speech with desired speaking style and emotion by transferring the style and emotion from reference speech recorded by other spea…
End-to-End Voice Conversion with Information Perturbation
Qicong Xie, Shan Yang, Yi Lei +2
The ideal goal of voice conversion is to convert the source speaker's speech to sound naturally like the target speaker while maintaining the linguistic content and the prosody of…